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Line of Best Fit

Line of Best Fit. Linear Regression. Entering Data : TI 30X. 2 nd DATA choose 2-VAR DATA (enter data and use down arrow) STAT VAR Arrow over to find a = b = r = The equation of the line is y = a x + b. Correlation Coefficient is r.

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Line of Best Fit

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  1. Line of Best Fit Linear Regression

  2. Entering Data : TI 30X • 2ndDATA choose 2-VAR • DATA (enter data and use down arrow) • STAT VAR • Arrow over to find • a = b = r = • The equation of the line is y = ax + b. • Correlation Coefficient is r. • To predict use a(predict #) + b. Estimated method

  3. Entering Data : TI 36X - Pro • DATA (type in data) • 2nd DATA • 2 VAR L1 L2 Frequency of 1 Calc • a = b = r = • The equation of the line is y = ax + b. • Correlation Coefficient is r. • To predict use a(predict #) + b. Estimated method • You can use the x variable button to find a and b

  4. Example 1: The table shows the total outstanding consumer debt (excluding home mortgages) in billions of dollars in selected years. (Data is from the Federal Reserve Bulletin.) Let x = 0 correspond to 1985. a) Find the regression equation appropriate for this data set. Round values to two decimal places.

  5. Example 1: • Find and interpret the slope of the regression equation in the context of the scenario. 79.86 represents the increase in consumer debt each year. • Find the approximate consumer debt in 1998. • Find the approximate consumer debt in 2008.

  6. Example 2: The table below shows the number of deaths per 100,000 people from heart disease in selected years. (Data is from the U.S. National Center for Health Statistics.) Let x = 0 correspond to 1960. a) Find the regression equation appropriate for this data set. Round values to two decimal places.

  7. Example 2: • Find and interpret the slope of the regression equation in the context of the scenario. -7.62 is the decrease in deaths caused by heart disease each year. • Find the approximate number of deaths due to heart disease in 1995. • Find the approximate number of deaths due to heart disease in 2008.

  8. Classwork Linear Regression

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